{"id":"W2338193250","doi":"10.2139/ssrn.2318157","title":"Optimal Price-Lead Time Menus for Queues with Customer Choice: Priorities, Pooling &amp; Strategic Delay","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Toronto","funders":"","keywords":"Pooling; Lead (geology); Queue; Lead time; Business; Microeconomics; Computer science; Operations research; Marketing; Industrial organization; Operations management; Economics; Engineering; Computer network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01319481,0.001480044,0.004489086,0.002680854,0.002126353,0.008183663,0.004216787,0.003310004,0.01272995],"category_scores_gemma":[0.03793415,0.002841094,0.001729554,0.002648827,0.002659157,0.007615543,0.003515789,0.004125352,0.001285806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00676077,"about_ca_system_score_gemma":0.006887733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006587637,"about_ca_topic_score_gemma":0.00595675,"domain_scores_codex":[0.9941031,0.002651456,0.0003567495,0.0007176687,0.0006852483,0.001485843],"domain_scores_gemma":[0.9610614,0.02783769,0.002339994,0.001312272,0.002452517,0.004996082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003723258,0.001581585,0.002435581,0.0004775137,0.0002040563,0.0002747609,0.0009335228,0.6182455,0.005381449,0.2879552,0.006889224,0.07189833],"study_design_scores_gemma":[0.0003721001,0.0003920175,0.0005431943,0.0000688756,0.00009388948,0.00004968769,0.0002119795,0.8893672,0.0008271301,0.1071378,0.0008183784,0.0001177553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2543065,0.001045428,0.7286792,0.001994765,0.000358442,0.0005855891,0.0005091353,0.0009897595,0.01153123],"genre_scores_gemma":[0.8991682,0.0004760424,0.09281138,0.0002409789,0.0001452695,0.0002581072,0.0001540439,0.0001678054,0.006578156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01319481,"threshold_uncertainty_score":0.06978166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105106937829519,"score_gpt":0.2351199781675051,"score_spread":0.2240689087892099,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}